{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# matplotlib绘图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "matplotlib概念上分为：\n",
    "1. pylab快速绘图：提供了类似matlab中的快速方便的交互式绘图函数；\n",
    "2. 脚本层：pyplot等大量matplotlib API；\n",
    "3. 绘图元素层：提供了面向对象和图形语法来构建图形的方式；\n",
    "    > artist.Artist：所有绘图元素的基类，该基类提供了绘图元素的基本属性，并提供了以obj.get\\_系列函数来获取属性、obj.set\\_系列函数来设置属性、setp(obj, '属性'， 值)、getp(obj)获取obj所有属性，getp(obj, '属性')获取指定属性。各绘图元素除了Artist共有的属性外，还带有自己特有的属性。\n",
    "    \n",
    "|artist通用属性| 属性用途|\n",
    "|--------------|---------|\n",
    "|alpha | 透明度，值在0到1之间，0为完全透明，1为完全不透明 |\n",
    "|animated | 布尔值，在绘制动画效果时使用 |\n",
    "|axes | 此Artist对象所在的Axes对象，可能为None |\n",
    "|clip_box | 对象的裁剪框 |\n",
    "|clip_on | 是否裁剪 |\n",
    "|clip_path | 裁剪的路径 |\n",
    "|contains | 判断指定点是否在对象上的函数 |\n",
    "|figure | 所在的Figure对象，可能为None |\n",
    "|label | 文本标签 |\n",
    "|picker | 控制Artist对象选取 |\n",
    "|transform | 控制偏移旋转 |\n",
    "|visible | 是否可见 |\n",
    "|zorder | 控制绘图顺序 |\n",
    "|agg_filter|unknown|\n",
    "|gid|\tan id string|\n",
    "|path_effects|\tunknown|\n",
    "|rasterized|True、False、None|\n",
    "|sketch_params|\tunknown|\n",
    "|snap|\tunknown|\n",
    "|url|\ta url string|\n",
    "\n",
    "|Axes新增artist属性\t|属性描述|\n",
    "|-------------------|--------|\n",
    "|adjustable\t|‘box’、‘datalim’、‘box-forced’|\n",
    "|anchor|\tunknown|\n",
    "|aspect|\tunknown|\n",
    "|autoscale_on|\tunknown|\n",
    "|autoscalex_on|\tunknown|\n",
    "|autoscaley_on|\tunknown|\n",
    "|axes_locator|\tunknown|\n",
    "|axis_bgcolor|\tany matplotlib color - see colors()|\n",
    "|axisbelow|\tTrue 、False|\n",
    "|color_cycle|\tunknown|\n",
    "|figure|\tunknown|\n",
    "|frame_on|\tTrue、False|\n",
    "|navigate|  True、False|\n",
    "|navigate_mode|\tunknown|\n",
    "|position|\tunknown|\n",
    "|rasterization_zorder|\tunknown|\n",
    "|title|\tunknown|\n",
    "|xbound|\tunknown|\n",
    "|xlabel|\tunknown|\n",
    "|xlim|\tlength 2 sequence of floats|\n",
    "|xmargin|\tunknown|\n",
    "|xscale|‘linear’、‘log’、‘logit’、‘symlog’|\n",
    "|xticklabels|\tsequence of strings|\n",
    "|xticks|\tsequence of floats|\n",
    "|ybound|\tunknown|\n",
    "|ylabel|\tunknown|\n",
    "|ylim|\tlength 2 sequence of floats|\n",
    "|ymargin|\tunknown|\n",
    "|yscale|‘linear’、‘log’、‘logit’、‘symlog’|\n",
    "|yticklabels|\tsequence of strings|\n",
    "|yticks|\tsequence of floats|\n",
    "    \n",
    "    > 图形语法：如果说artist.Artist，表明了绘图元素及属性的继承关系，则图形语法表明了绘图元素的拓扑结构；绘图元素可分为简单类型和容器类型。简单类型的Artists绘图元素，例如Line2D、 Rectangle、 Text、AxesImage 等等。而容器类型则可以包含許多简单类型的Artists，使它們组织成一個整体，例如Axis、 Axes、Figure等。绘图元素，除了set\\_和get\\_及属性之外（从artist.Artist继承，包括自己定义的），还包括一系列添加其他绘图元素的函数，还有管理这些绘图元素的数据结构。\n",
    "\n",
    "    \n",
    "|Axes创建绘图元素方法\t|被创建的绘图元素\t|管理绘图元素的属性|\n",
    "|----|--------|----|\n",
    "|annotate\t|Annotate\t|texts|\n",
    "|bars\t|Rectangle\t|patches|\n",
    "|errorbar\t|Line2D, Rectangle\t|lines,patches|\n",
    "|fill\t|Polygon\t|patches|\n",
    "|hist\t|Rectangle\t|patches|\n",
    "|imshow\t|AxesImage\t|images|\n",
    "|legend\t|Legend\t|legends|\n",
    "|plot\t|Line2D\t|lines|\n",
    "|scatter\t|PolygonCollection\t|Collections|\n",
    "|text\t|Text\t|texts|\n",
    "4. 后端层：\n",
    "    > backend_bases.FigureCanvas：图形的绘制领域\n",
    "    \n",
    "    > backend_bases.Renderer：知道如何在FigureCanvas上如何绘制\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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YCCEUOEIIOYfrjiuT5Vmog4ODjC9CCAWOEELODAwM2Cx662Yp2JyI6tZ/SircobdYLLhO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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename=u\"..\\images\\matplotlib绘图元素拓扑结构.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## matplotlib配置文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'd:\\\\Anaconda2\\\\lib\\\\site-packages\\\\matplotlib\\\\mpl-data\\\\matplotlibrc'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from pylab import *\n",
    "matplotlib.matplotlib_fname()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 动态配置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "mpl.rcParams['lines.linewidth'] = 2\n",
    "mpl.rcParams['lines.color'] = 'r'\n",
    "mpl.rc('lines', linewidth=2, color='r') #或者"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 图形语法\n",
    "    图形元素包括：figure绘图对象（容器）、Axes子图、Subplot子区，类似R中分面\n",
    "    Axes or Subplot又包括：XAxis/YAxis坐标系统、title子图标题、text子图文字、annotate注解等\n",
    "    坐标系统又包括：tick刻度、tick lable刻度注释、xlabel/ylabel轴标题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 创建绘图对象（容器）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 5, 6]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6c44438>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3b85fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3bc9128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6b655c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6b65cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6c44438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#例1\n",
    "%matplotlib inline\n",
    "from pylab import *\n",
    "figure()       #创建第一个绘图对象\n",
    "figure(2)      #创建第二个绘图对象\n",
    "figure(3)      #创建第三个绘图对象\n",
    "figure(5)      #创建第四个绘图对象\n",
    "figure()       #创建第五绘图对象\n",
    "print get_fignums()  #返回对象个数\n",
    "gcf()          #f返回当前绘图对象，这里指向第一个"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 创建子图和子区"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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V3QSM1uqPm+jt8WqPV3u8SieIlj1eH3r2KXAW8DTwnqraNWZ/Ng3pedxFxrbHq7RKbXq8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\njwKqJ0H3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6b56eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#例1\n",
    "subplot(221)   #创建2x2格子1子区，默认创建绘图对象\n",
    "subplot(224)   #创建2x2格子4子区，在已有绘图对象中\n",
    "grid()         #当前子区中创建网格"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x6f481d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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m+40Nc9EwFw1z0Y1Vi/zYjNftwNuA60eXFp627zPAfV0HKUmaTSczXkePfxj4T+By4BtV\n9Q9TjmVPXpLWqPcZr0kuAN5TVV8AZgpEktS9rma83gaM9+pPWuid8eqM18n18ceWJZ4+1854dcbr\n8dfCss14ffz4XeA84AXgA1W1Z+JYtmtG9jkQ4QRz0TAXDXPR6H3G68T+LwFftycvSd3ofcbr5K/M\nEogkqXutvidfVf9YVb9XVW+pqs+MHvvbKQWeqvpf097F66XG+9GnO3PRMBcNc9ENz3iVpAHz2jWS\ntOS8do0kaSqLfE/sNzbMRcNcNMxFNyzykjRg9uQlacnZk5ckTWWR74n9xoa5aJiLhrnohkVekgbM\nnrwkLTl78pKkqTqZ8ZpkZ5KHRrf7k7y9+1CHxX5jw1w0zEXDXHSjqxmvjwN/UFWXAp8G/m/XgUqS\n1q6zGa9j+18DPFxVb5zyM3vykrRGvc94nfB+4N5ZgpEkdavTD16TXAns4qXzXjWF/caGuWiYi4a5\n6EabQd5HgY1j6zeMHnuJJJcAu4EdVfXcyQ7mIG/Xk+vjliWePtcHDx5cqnj6XB88eHCp4lnket+C\nB3mvOuM1yUbg28ANVbX/FMeyJy9Ja7QMM14/CZwLfD5JgGNVtWWWgCRJ3elkxmtV/e+qem1VXVZV\n77DAr26yVXE6MxcNc9EwF93wjFdJGjCvXSNJS85r10iSprLI98R+Y8NcNMxFw1x0wyIvSQNmT16S\nlpw9eUnSVBb5nthvbJiLhrlomItuWOQlacDsyUvSkrMnL0maqpMZr6M9n0vyaJKDSTZ3G+bw2G9s\nmIuGuWiYi250MuM1yTXARVX1FuAm4ItziHVQjl8rW+ZinLlomItutHknvwV4tKqeqKpjwN3Auyf2\nvBv4MkBVfQfYkOT8TiMdmOeff77vEJaGuWiYi4a56EZXM14n9xydskeStGB+8NqTn/70p32HsDTM\nRcNcNMxFN9qM/9sK3FJVO0brj7MyEeqzY3u+COytqr8frQ8D/7Oqnpo4lt+flKQZzG38H3AAeHOS\nC1mZ8XodcP3Enj3AXwB/P/pH4fnJAr+eICVJs+lkxmtVfSvJu5IcAV4Ads03bElSGws941WStFhz\n+eDVk6caq+Uiyc4kD41u9yd5ex9xLkKb58Vo3+VJjiW5dpHxLVLL18i2JA8m+X6SvYuOcVFavEbO\nSbJnVCseTnJjD2HOXZI7kzyV5NAp9qy9blZVpzdW/uE4AlwI/BZwENg0seca4Juj++8E9ncdxzLc\nWuZiK7BhdH/H6ZyLsX3fBr4BXNt33D0+LzYAPwBeP1qf13fcPebiE8Ctx/MAPAuc2Xfsc8jFFcBm\n4NBJfj5T3ZzHO3lPnmqsmouq2l9Vvxot9zPc8wvaPC8APgR8FXh6kcEtWJtc7ATuqaqjAFX1zIJj\nXJQ2uSjg7NH9s4Fnq+o3C4xxIarqfuC5U2yZqW7Oo8h78lSjTS7GvR+4d64R9WfVXCS5AHhPVX0B\nGPI3sdo8Ly4Gzk2yN8mBJDcsLLrFapOL24G3JnkSeAj48IJiWzYz1c02X6HUAiS5kpVvJV3Rdyw9\nug0Y78kOudCv5kzgMuAq4FXAA0keqKoj/YbVi+3Ag1V1VZKLgH9OcklV/Uffgb0czKPIHwU2jq3f\nMHpscs8bV9kzBG1yQZJLgN3Ajqo61Z9rL2dtcvH7wN1Jwkrv9Zokx6pqz4JiXJQ2ufg58ExV/Rr4\ndZJ/BS5lpX89JG1ysQu4FaCqHkvyE2AT8L2FRLg8Zqqb82jXnDh5KslZrJw8Nfki3QO8F06cUTv1\n5KkBWDUXSTYC9wA3VNVjPcS4KKvmoqp+d3T7HVb68n8+wAIP7V4jXwOuSHJGkley8kHbIwuOcxHa\n5OIJ4A8BRj3oi4HHFxrl4oST/wU7U93s/J18efLUCW1yAXwSOBf4/Ogd7LGq2tJf1PPRMhcv+ZWF\nB7kgLV8jh5PcBxwCXgR2V9UPewx7Llo+Lz4N3DX21cKPVtUvewp5bpJ8BdgGvDbJz4CbgbNYZ930\nZChJGjCvQilJA2aRl6QBs8hL0oBZ5CVpwCzykjRgFnlJGjCLvCQNmEVekgbsvwCdDf4CjJ20hQAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6f482e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#例2\n",
    "subplots()      #创建1个子区，默认创建绘图对象\n",
    "subplots(2)     #创建2个子区，同时创建新的绘图对象，注意与subplot区别\n",
    "grid()          #当前子区中创建网格"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._axes.Axes at 0x7b5d6d8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Wrdi0aROpqamFwypL/cyLiIiIgIqiJJyZnQm85e4XRjnWHxgaKorSE3i6tKIo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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x78691d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#例3\n",
    "axes([.65, .6, .2, .2])  #默认创建绘图对象，创建子图,[left, bottom, width, height]\n",
    "axes([.75, .7, .2, .2])  #相同绘图对象中，再次创建子图\n",
    "axes([.85, .8, .2, .2], axisbg='g')           #属性，设置背景色\n",
    "axes([.95, .9, .2, .2], frameon=False)        #属性，不显示外框\n",
    "axes([1.25, .9, .2, .2], polar=True)          #属性，极坐标\n",
    "axes([1.55, .6, .6, .9], aspect='equal')      #属性，y/x比例，equal、auto、number\n",
    "axes([2.15, .6, .6, .9], aspect=2)            #属性，y/x比例，2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.PolarAxesSubplot at 0x6d7e710>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zG6paSO0R0PxZinEGUStqvO8stqxzrqXcZgju+EJEOonItyIyw9lRdMxSl74N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\nyO+ffZa4qTzZVpPSjSQdOsDIkanjJUvyT4IcfHC6zFkolB77fOihdDm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BfCMyIXA+JF6A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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3b85eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#例4\n",
    "subplot(221,frameon=False,aspect=2,polar=True,axisbg='g')  #axes属性，同样适用于subplot,但不适用于subplots\n",
    "subplot(222,frameon=True,aspect=2,polar=True,axisbg='w')\n",
    "subplot(223,frameon=True,aspect=2,polar=True,axisbg='r')\n",
    "subplot(224,frameon=True,aspect=2,polar=True,axisbg='y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 快速绘图函数 - plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x8328eb8>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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otRwiOW7OVE4TZ4JmzuVM5TRxprLKFPXlwH9m5g8y8xfA3wHvWunCplV0E//HOFM5TZwJ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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7874400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(np.arange(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot图类型\n",
    "## 直方图（又称柱状图）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  2.,   2.,   0.,   4.,   1.,   6.,   7.,   4.,   5.,  11.,   4.,\n",
       "         10.,  14.,  13.,   5.,   4.,   0.,   3.,   2.,   2.,   0.,   0.,\n",
       "          0.,   0.,   1.]),\n",
       " array([-2.68188837, -2.44122534, -2.20056232, -1.95989929, -1.71923626,\n",
       "        -1.47857323, -1.23791021, -0.99724718, -0.75658415, -0.51592112,\n",
       "        -0.27525809, -0.03459507,  0.20606796,  0.44673099,  0.68739402,\n",
       "         0.92805704,  1.16872007,  1.4093831 ,  1.65004613,  1.89070915,\n",
       "         2.13137218,  2.37203521,  2.61269824,  2.85336126,  3.09402429,\n",
       "         3.33468732]),\n",
       " <a list of 25 Patch objects>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAEACAYAAABF+UbAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCHEASIwQB4DECHEASOz/AfF6Vw2YtBN6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8347ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = np.random.randn(100)\n",
    "hist(y, 10)\n",
    "hist(y, 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 直条图（又称条形图）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW8AAAEACAYAAAB8nvebAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6H8BV4dS3ayjp4oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8c38080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar([1, 2, 3], [3, 2, 5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 饼状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x9223cc0>,\n",
       "  <matplotlib.patches.Wedge at 0x92329e8>,\n",
       "  <matplotlib.patches.Wedge at 0x92426d8>],\n",
       " [<matplotlib.text.Text at 0x92325f8>,\n",
       "  <matplotlib.text.Text at 0x92422e8>,\n",
       "  <matplotlib.text.Text at 0x9242f98>])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x8c2feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [45, 35, 20]                    #比例\n",
    "figure(figsize=(10,8))\n",
    "subplot(341)\n",
    "labels = ['Cats', 'Dogs', 'Fishes']\n",
    "pie(x, labels=labels)              #属性，标签\n",
    "subplot(342)\n",
    "pie(x, colors=['w','w','w'])       #属性，颜色\n",
    "subplot(343)\n",
    "pie(x, shadow=True)                #属性，阴影，不明显"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
